Multipath reflection has great influence on the meter-wave radar low-elevation height-finding. In this paper, a computationally efficient method is presented fully using the information included in the received data covariance matrix. This method is proposed according to the spatial smoothing concept and the propagator operator method. The presented method constructs new forward and backward matrices based on the spatial smoothing idea, and then summing the obtained forward and backward matrices obtains the noise subspace with the propagator operator method. This algorithm estimates DOAs without the need to decorrelate and eigen-decompose. Therefore, the method has good estimation performance for the meter-wave radar height-finding with a small number of snapshots and at low SNR. Simulation experiments and real data processing results both demonstrate the effectiveness of the proposed method in the meter-wave radar low-elevation height-finding applications.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Computationally Efficient Method in the Meter-Wave Radar Low-Elevation Height-Finding Applications


    Beteiligte:
    Hu, Xiao-qin (Autor:in) / Chen, Jian-wen (Autor:in) / Chen, Hui (Autor:in) / Wang, Yong-liang (Autor:in)


    Erscheinungsdatum :

    2008-05-01


    Format / Umfang :

    363970 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Use of a Multipath Model in the Meter-wave Radar Height-finding Applications

    Xiao-qin, Hu / Jian-wen, Chen / Yong-liang, Wang | IEEE | 2008


    Linearized Lambert's Solution for Computationally Efficient Applications

    McMahon, Jay W. / Scheeres, Daniel J. | AIAA | 2014


    Computationally Efficient Multibody Simulations

    Ramakrishnan, J. / Kumar, M. / National Aeronautics and Space Administration | British Library Conference Proceedings | 1994


    COMPUTATIONALLY EFFICIENT BAYESIAN OPTIMIZATION FOR MULTI-OBJECTIVE INDUSTRIAL APPLICATIONS

    Pandita, Piyush / Ghosh, Sayan / Wang, Liping | TIBKAT | 2021